Studying Metabolic Brain Connectivity Using 2-Deoxy-2-[18F]Fluoro-D-Glucose Dynamic Positron Emission Tomography at the Single-subject Level

PET imaging with [18F]-FDG is widely used to study how diseases affect the brain by measuring glucose metabolism, which reflects cellular activity. Particularly, the assessment of metabolic brain connectivity can highlight how different brain regions functionally interact in relation to the tracer uptake.

However, most brain network studies rely on group-level analysis because of the static nature of traditional PET imaging, making it hard to track changes within individuals over time. To overcome this limitation, a protocol for dynamic PET imaging was reported, enabling single-subject analysis crucial for studying brain network disorders and disease progression, such as epilepsy or dementia.

Dynamic PET data of the rat brain are acquired with the β-CUBE (PET) using 2-deoxy-2-[18F]fluoro-D-glucose ([18F]-FDG) as tracer. After starting the 60-minute acquisition, the tracer was injected as a bolus with approximately 20 MBq [18F]-FDG.

PET data were corrected for radionuclide decay and reconstructed with the ordered subset expectation maximization 3-dimensional (OSEM-3D) algorithm. No attenuation correction was performed.

For the dynamic reconstruction, the data was reconstructed into thirty 2-minute time frames using 30 iterations for each frame, an isometric voxel size of 400 µm, and an energy window of 30% centered on the 511 keV photopeak.

A brain atlas divided into multiple volumes of interest (VOIs) is used to extract time-activity curves for each region, which are then compared to each other by calculating the Pearson correlation between every pair of VOIs.

Using a 60-minute dynamic [18F]-FDG PET protocol in rats, the experiment successfully generated individual metabolic connectivity matrices by correlating tracer uptake between brain regions over time. The protocol focused on true metabolic activity, excluding early perfusion-dominated frames and optimizing time frame length.

The resulting data enabled the construction of brain network graphs for each subject, supporting single-subject analysis of brain connectivity.

The authors emphasize that several methodological factors need to be taken into account for this approach, including the accuracy of tracer injection, the type of anesthesia used, and the spatial resolution of the brain atlas.

Despite limitations, the protocol demonstrated that dynamic PET allows for reliable within-subject assessment of metabolic brain connectivity, exemplified in figure below.

Figure adapted from Lajtos, Melissa, et al. Journal of Visualized Experiments (JoVE) 215 (2025): e67458. Adapted Px Rat (W. Schiffer) atlas. VOIs of the rat atlas on top of the acquired PET image.